Social Simulation as a meeting place: report of SSC 2018 Stockholm

Last month, August 20-24, Stockholm provided the glorious scenery for the 14th annual conference of ESSA, the European Social Simulation Association. 14 years is an age at which we start to look in the mirror, and that was indeed the conference theme. What is Social Simulation, and where is it headed? I’ll briefly present my observations and reflections.

First, I was happy to see that there is life in this community. Some of the founders are no longer with us, or not in Stockholm, but their legacy is alive, and a multifarious, clever lot of researchers are ready to continue the journey. Actually, rather suddenly I find myself an older man in the community, and I consider that very good news.

Second, there is quality. During all the week, I have not had to endure one single poor, boring talk. There is real content and it is being delivered very well. The organizers also did their bit by providing lively formats.

Third, there is a sense of direction. Our community aims for relevance, and rigour only in so far as it serves relevance, not for its own sake. In the mirror, we see a responsible teenager discipline, ready to take on the world.

It would be infeasible for me to try and summarise all the sessions that I have attended. Instead, let me share the meta-model of our discipline that presented itself to me on Friday (see figure 1).

Figure 1: Social Simulation as a meeting place

The main message of this figure is that social simulation, as it appeared at SSC Stockholm, is a meeting place of three very different worlds:

There are always two levels: the agents doing their things, and the resulting system-level patterns of behaviour. Agent-based models connect these two levels through their mechanisms.

These could also either be about agents, or about system-level patterns.

Real life. Once more, there are agents here, called in this case ‘stakeholders’, and there are those who might know about system behaviour, called ‘experts’.

Not all researchers, nor all disciplines, have equal experience with all three worlds. You, reader, are probably drawn more to some than to others. But it is my conviction that we need all three to keep our discipline fruitful. Also, that we social simulators have an essential contribution to make in creating our models. Notably, what we do is:

We define the focus and scope of models

We select or think up mechanisms for agents

We select from among the six possible actions in figure 1, to create a convincing message to our target community.

This last point deserves some thought, because we need an audience. Target communities tend to prefer one of the three worlds, so ‘one story does not fit all’. In their 1995 seminal book ‘Artificial Societies’ (that keeps being reprinted), Nigel Gilbert and Rosaria Conte deplore the demise of theory development in sociology, and state that ‘a wide gap continues to exist between empirical research and theorizing’ (p. 5). In my view these worlds are still wide apart. Perhaps the emergence of the Web has, since the appearance of that book, tilted the balance even further in favour of data. Yet without theory, data is meaningless. In 2012, Flaminio Squazzoni, in his book ‘Agent based computational sociology’, put this into words nicely. He concluded (p. 172) “Tighter links between observations and theory are productive, if and only if they are mediated by formalized models.” Quite so. It would appear that in this quote, Flaminio assumes that these observations are taken from real life. After SSC 2018, however, I have become convinced that there is not necessarily unity between the world of stakeholders and experts on the one hand, and the world of surveys and experiments on the other. In fact, agent-based models can help to reconcile the two.

Perhaps I can attempt a brief discussion of each day’s keynote, at the hand of figure 1. I found the mix of keynotes inspiring.

On Tuesday, it was real-world time. Bruce Edmonds argued for putting as much real-life as possible into agent-based models, calling it “context”. My hunch is that what Bruce calls the “social context” can be understood in generic terms and bring this field a lot further. A big question is what I’d like to call the zooming factor: the more you zoom in, the more you need to know about context; the more you zoom out, the more you need theory for achieving generic validity.

On Wednesday, the model ruled. Milena Tsvekova described what I call ‘Procrustes experiments’, where experiments follow the design of an ABM. She granted a place for real life: “the comparison between ABM and experiment is not perfect, because it depends on how you frame the situation”.

Thursday was theory day. Julie Zahle made us think and talk about our method and the worldview behind it.

To avoid boring you all stiff with more detail, let me just summarize the general atmosphere by giving you a brief list of tongue breakers from SSC 2018: gregariousness, heteroskedasticiy, methodological, Valdemars Udde, Vapnik Chervonenkis. See you in Mainz (23-27 September 2019)!

Hofstede, G.J. (2018) Social Simulation as a meeting place: report of SSC 2018 Stockholm. Review of Artificial Societies and Social Simulation, 18th September 2018. https://rofasss.org/2018/09/19/gh